repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/modeling.py | # DeepSpeed note, code taken from commit 3d59216cec89a363649b4fe3d15295ba936ced0f
# https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/LanguageModeling/BERT/modeling.py
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPOR... | 72,132 | 44.366667 | 141 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/alexnet_model.py | import pytest
import torch
import torch.nn as nn
import torch.nn.functional as F
import deepspeed
import deepspeed.comm as dist
import deepspeed.runtime.utils as ds_utils
from deepspeed.runtime.pipe.module import PipelineModule, LayerSpec
class AlexNet(nn.Module):
def __init__(self, num_classes=10):
super... | 5,158 | 31.043478 | 83 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/simple_model.py | import os
import json
import argparse
import torch
from deepspeed.pipe import PipelineModule, LayerSpec
from deepspeed.moe.layer import MoE
import deepspeed.comm as dist
class SimpleModel(torch.nn.Module):
def __init__(self, hidden_dim, empty_grad=False, nlayers=1):
super(SimpleModel, self).__init__()
... | 10,350 | 35.319298 | 86 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/common.py | import os
import time
import inspect
from abc import ABC, abstractmethod
from pathlib import Path
import torch
import torch.multiprocessing as mp
import deepspeed
import deepspeed.comm as dist
from torch.multiprocessing import Process
import pytest
from _pytest.outcomes import Skipped
from _pytest.fixtures import Fix... | 12,402 | 36.929664 | 106 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/util.py | import torch
from deepspeed.git_version_info import torch_info
def required_torch_version():
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torch.__version__.split('.')[1])
if TORCH_MAJOR >= 1 and TORCH_MINOR >= 8:
return True
else:
return False
def bf16_requir... | 1,649 | 28.464286 | 83 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/modelingpreln.py | # DeepSpeed note, code taken from commit 3d59216cec89a363649b4fe3d15295ba936ced0f
# https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/LanguageModeling/BERT/modeling.py
# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPOR... | 76,572 | 44.443917 | 141 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/megatron_model.py | import torch
import os
import sys
import math
from .common import get_test_path
from deepspeed.pipe import PipelineModule, LayerSpec
def get_megatron_version():
p = os.popen("pip list --format=columns | grep megatron-lm")
pip_list = p.read()
assert 'megatron-lm' in pip_list, 'Please install Megatron-LM b... | 4,029 | 33.741379 | 105 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/multi_output_model.py | import torch
class MultiOutputModel(torch.nn.Module):
def __init__(self, hidden_dim, weight_value):
super(MultiOutputModel, self).__init__()
self.linear = torch.nn.Linear(hidden_dim, hidden_dim, bias=False)
self.linear.weight.data.fill_(weight_value)
self.cross_entropy_loss = torch... | 1,402 | 32.404762 | 87 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/checkpoint/test_zero_optimizer.py | import deepspeed
from deepspeed.ops.op_builder import CPUAdamBuilder
from unit.common import DistributedTest, DistributedFixture
from unit.simple_model import *
from unit.util import required_minimum_torch_version
from unit.checkpoint.common import *
import pytest
class TestZeROCheckpoint(DistributedTest):
wor... | 17,789 | 37.75817 | 110 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/checkpoint/test_pipeline.py | from deepspeed.runtime.checkpoint_engine.torch_checkpoint_engine import TorchCheckpointEngine
from unit.common import DistributedTest
from unit.simple_model import *
from unit.checkpoint.common import checkpoint_correctness_verification
import pytest
class TestPipelineCheckpoint(DistributedTest):
world_size = 4... | 4,043 | 36.444444 | 99 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/checkpoint/test_sparse.py | import deepspeed
from unit.common import DistributedTest
from unit.simple_model import *
import pytest
class TestSparseCheckpoint(DistributedTest):
world_size = 2
@pytest.mark.parametrize(["to_save_model_has_embedding",
"to_save_model_sparse"],
[
... | 3,996 | 41.073684 | 109 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/checkpoint/common.py | import os
import torch
import numbers
import deepspeed
from deepspeed.runtime.zero.stage_1_and_2 import DeepSpeedZeroOptimizer
from deepspeed.runtime.fp16.fused_optimizer import FP16_Optimizer
from deepspeed.runtime.fp16.unfused_optimizer import FP16_UnfusedOptimizer
from deepspeed.runtime.zero.stage3 import DeepSpeed... | 10,043 | 44.863014 | 137 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/checkpoint/test_moe_checkpoint.py | from deepspeed.moe.utils import split_params_into_different_moe_groups_for_optimizer
from unit.common import DistributedTest
from unit.simple_model import *
from unit.util import required_torch_version
from unit.checkpoint.common import checkpoint_correctness_verification
import pytest
class TestMoECheckpoint(Dist... | 4,290 | 38.731481 | 88 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/profiling/flops_profiler/test_flops_profiler.py | import torch
import pytest
import deepspeed
from deepspeed.profiling.flops_profiler import get_model_profile
from unit.simple_model import SimpleModel, random_dataloader
from unit.common import DistributedTest
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torch.__version__.split('.')[1])
pytestm... | 4,117 | 31.171875 | 81 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/compression/test_compression.py | import torch
import pytest
import random
import numpy as np
from unit.megatron_model import get_gpt2_model
from deepspeed.compression.compress import init_compression
from unit.modeling import BertConfig
from unit.modelingpreln import BertEncoder as BertEncoderPreln
from deepspeed.compression.basic_layer import LinearL... | 9,909 | 36.824427 | 125 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/test_data.py | from deepspeed.utils import RepeatingLoader
import torch
import pytest
import deepspeed
from unit.common import DistributedTest
from unit.simple_model import SimpleModel, random_dataset
def test_repeating_loader():
loader = [1, 2, 3]
loader = RepeatingLoader(loader)
for idx in range(50):
assert n... | 2,096 | 35.789474 | 92 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/test_runtime_utils.py | import torch
from torch._utils import _flatten_dense_tensors
import deepspeed.comm as dist
import pytest
import deepspeed.runtime.utils as ds_utils
import deepspeed.utils.groups as groups
from unit.common import DistributedTest
def test_call_to_str():
c2s = ds_utils.call_to_str
assert c2s('int') == 'int()'... | 2,480 | 32.08 | 103 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/test_autocast.py | import pytest
import torch
from deepspeed.runtime.zero.linear import LinearModuleForZeroStage3
@pytest.mark.parametrize('half_op', [False, True])
def test_missing_amp_autocast(tmpdir, half_op):
hidden_dim = 4
if half_op:
input = torch.randn(hidden_dim).cuda().half()
ds_linear = LinearModuleFor... | 1,942 | 30.33871 | 83 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/test_lr_schedulers.py | import torch
import deepspeed
import pytest
from unit.common import DistributedTest
from unit.simple_model import SimpleModel, random_dataloader
from deepspeed.runtime.lr_schedules import LR_RANGE_TEST, LR_RANGE_TEST_MIN_LR, LR_RANGE_TEST_STEP_RATE, LR_RANGE_TEST_STEP_SIZE, LR_RANGE_TEST_STAIRCASE
from deepspeed.runtim... | 17,551 | 37.660793 | 153 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/test_multi_output_model.py | import torch
import deepspeed
from pytest import approx
from unit.common import DistributedTest
from unit.multi_output_model import MultiOutputModel, multi_output_dataloader
class TestTwoOutputModel(DistributedTest):
world_size = 1
def test(self, tmpdir):
grad_accumulation_steps = 2
micro_bat... | 5,400 | 39.007407 | 103 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/test_ds_config_dict.py | # A test on its own
import torch
import pytest
import json
import argparse
from deepspeed.runtime.zero.config import DeepSpeedZeroConfig
from unit.common import DistributedTest, get_test_path
from unit.simple_model import SimpleModel, create_config_from_dict, random_dataloader
import deepspeed.comm as dist
# A test ... | 9,348 | 34.547529 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/test_ds_initialize.py | import pytest
from typing import Callable
import torch
from torch.optim import Optimizer, Adam, AdamW
from torch.optim.lr_scheduler import _LRScheduler, LambdaLR
from unit.simple_model import SimpleModel, random_dataloader
from unit.common import DistributedTest
from unit.util import required_torch_version, bf16_requi... | 10,303 | 37.883019 | 136 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/activation_checkpointing/test_activation_checkpointing.py | # TODO: add tests with model parallelism for activation partitioning and other features.
import pytest
import torch
import deepspeed
from copy import deepcopy
from unit.common import DistributedTest
ckpt = deepspeed.checkpointing.checkpoint
def _compute(module, *inputs, do_checkpoint=False):
if do_checkpoint:
... | 7,680 | 27.984906 | 88 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/comm/test_coalesced_collectives.py | """unit tests for coalesced collectives"""
import torch
import deepspeed.comm as dist
from deepspeed.runtime.comm.coalesced_collectives import reduce_scatter_coalesced
from unit.common import DistributedTest
class TestReduceScatterCoalesced(DistributedTest):
world_size = 2
def test_single_input(self):
... | 2,333 | 36.047619 | 88 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/sparse_tensor/test_averaging_sparse_gradients.py | import torch
import deepspeed
from unit.common import DistributedTest
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
self.emb = torch.nn.EmbeddingBag(10, 3, mode="sum", sparse=True)
self.linear = torch.nn.Linear(3, 1)
def forward(self, x, offsets):
return... | 2,514 | 30.4375 | 83 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/sparse_tensor/test_csr.py | import torch
import random
from deepspeed.runtime.sparse_tensor import SparseTensor
def test_csr_addition_self():
row_count = 10
random.seed(1234)
x = torch.ones(1, 5)
for i in range(row_count - 1):
if random.random() > 0.75:
x = torch.cat([x, torch.ones(1, 5)])
else:
... | 1,230 | 23.137255 | 56 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/sparse_tensor/test_sparse_grads.py | import torch
import deepspeed
from unit.common import DistributedTest
import deepspeed.utils.groups as groups
class Model(torch.nn.Module):
def __init__(self):
super().__init__()
self.emb = torch.nn.EmbeddingBag(10, 3, mode="sum", sparse=True)
self.linear = torch.nn.Linear(3, 1)
def ... | 2,331 | 30.945205 | 87 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/half_precision/test_bf16.py | import torch
import deepspeed
import pytest
from deepspeed.ops.adam import FusedAdam
from unit.common import DistributedTest
from deepspeed.ops.op_builder import CPUAdamBuilder
from unit.simple_model import SimpleModel, SimpleOptimizer, random_dataloader
from unit.util import bf16_required_version_check
from deepspeed ... | 12,845 | 35.08427 | 141 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/half_precision/test_dynamic_loss_scale.py | import torch
import deepspeed
import numpy as np
from unit.common import DistributedTest
from unit.simple_model import SimpleModel
def run_model_step(model, gradient_list):
for value in gradient_list:
for p in model.parameters():
p.grad = torch.empty_like(p, dtype=p.dtype)
p.grad.f... | 10,436 | 36.543165 | 87 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/half_precision/test_fp16.py | import torch
import deepspeed.comm as dist
import deepspeed
import pytest
from deepspeed.ops.adam import FusedAdam
from unit.common import DistributedTest
from deepspeed.ops.op_builder import CPUAdamBuilder
from unit.simple_model import SimpleModel, SimpleOptimizer, random_dataloader, SimpleMoEModel, sequence_dataloade... | 29,712 | 34.928658 | 114 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/half_precision/onebit/test_onebit.py | import torch
import torch.nn as nn
import deepspeed.comm as dist
import deepspeed
import pytest
import copy
import os
import numpy as np
from deepspeed.runtime.pipe.topology import PipeDataParallelTopology
from deepspeed.ops.op_builder import OpBuilder
from deepspeed.runtime.pipe.module import PipelineModule
from unit... | 45,336 | 33.714395 | 117 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/zero/test_zero.py | import math
from typing import Dict, List, Set
import pytest
import deepspeed.comm as dist
import torch
from torch import Tensor
from torch.nn import Linear, Module
from torch.nn.modules.container import ModuleList
from torch.nn.modules.loss import L1Loss
from torch.nn.parameter import Parameter
from unit.common impor... | 48,482 | 35.841185 | 166 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/zero/test_zero_tiled.py | import copy
import torch
from deepspeed.runtime.zero.tiling import TiledLinear, TiledLinearReturnBias
import pytest
@pytest.mark.parametrize('in_splits,out_splits', [(1, 1), (2, 2), (5, 5), (32, 32)])
def test_tiled_init(in_splits, out_splits):
in_f = 32
out_f = 40
base = torch.nn.Linear(in_f, out_f, bi... | 6,267 | 35.44186 | 113 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/zero/test_zero_context.py | import os
from types import SimpleNamespace
import torch
import pytest
import deepspeed
from deepspeed.runtime.zero.partition_parameters import ZeroParamStatus, partitioned_param_data_shape
import deepspeed.comm as dist
from unit.common import DistributedTest, get_master_port
def setup_serial_env():
# Setup fo... | 12,414 | 30.35101 | 113 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/utils/test_partition.py | import pytest
import torch
import deepspeed.comm as dist
from deepspeed.runtime.utils import partition_uniform
from deepspeed.runtime.utils import partition_balanced
from deepspeed.runtime.utils import prefix_sum_inc
from deepspeed.runtime.utils import PartitionedTensor
from unit.common import DistributedTest
clas... | 4,754 | 23.384615 | 91 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/pipe/test_topology.py | import pytest
import torch
import deepspeed.comm as dist
from deepspeed.runtime.pipe.topology import PipelineParallelGrid as Grid
from deepspeed.runtime.pipe.topology import ProcessTopology as Topo
from deepspeed.runtime.pipe.topology import _prime_factors
from unit.common import DistributedTest
def test_topology_... | 8,104 | 35.345291 | 87 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/runtime/pipe/test_pipe.py | import copy
import torch.nn as nn
import pytest
import deepspeed.comm as dist
from deepspeed.runtime.pipe.topology import PipeDataParallelTopology
from deepspeed.runtime.pipe.module import PipelineModule
from unit.alexnet_model import AlexNetPipe, train_cifar
from unit.common import DistributedTest
PipeTopo = PipeDat... | 4,127 | 33.983051 | 129 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/moe/test_moe_tp.py | import torch
import deepspeed
import pytest
from unit.common import DistributedTest
from unit.util import required_torch_version
from deepspeed.moe.layer import MoE
class MPU():
def __init__(self, tp_world_size):
self.rank = deepspeed.comm.get_rank()
self.world_size = deepspeed.comm.get_world_size... | 3,413 | 34.195876 | 88 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/moe/test_moe.py | import torch
import deepspeed
import pytest
from unit.common import DistributedTest
from unit.simple_model import SimplePRMoEModel, SimpleMoEModel, sequence_dataloader
from unit.util import required_torch_version
@pytest.mark.parametrize("ep_size", [2, 4])
@pytest.mark.parametrize("use_residual", [True, False])
class... | 3,051 | 35.771084 | 88 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/model_parallelism/test_configurable_parallel_pp.py | import os
import torch
import deepspeed
import pytest
import random
import numpy as np
import deepspeed.comm as dist
from unit.common import DistributedTest, DistributedFixture
from unit.megatron_model import get_megatron_version
from unit.megatron_model import MockGPT2ModelPipe as GPT2ModelPipe
from deepspeed.utils im... | 11,527 | 37.684564 | 141 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/model_parallelism/test_configurable_parallel_mp.py | import os
import torch
import deepspeed
import pytest
import random
import numpy as np
import deepspeed.comm as dist
from unit.common import DistributedTest, DistributedFixture
from unit.megatron_model import get_gpt2_model, get_megatron_version
TORCH_MAJOR = int(torch.__version__.split('.')[0])
TORCH_MINOR = int(torc... | 6,036 | 34.304094 | 143 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/comm/test_dist.py | import os
import torch
import deepspeed.comm as dist
import deepspeed
from unit.common import DistributedTest, DistributedFixture, get_master_port
from unit.simple_model import SimpleModel
import pytest
class TestInit(DistributedTest):
world_size = 3
def test(self):
assert dist.is_initialized()
... | 6,001 | 30.424084 | 94 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/utils/test_init_on_device.py | import torch
import pytest
from unit.simple_model import SimpleModel
from deepspeed import OnDevice
from packaging import version as pkg_version
@pytest.mark.parametrize('device', ['meta', 'cuda:0'])
def test_on_device(device):
if device == "meta" and pkg_version.parse(
torch.__version__) < pkg_versio... | 612 | 29.65 | 71 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/inference/test_inference_config.py | import pytest
import torch
import deepspeed
from unit.common import DistributedTest
from unit.simple_model import create_config_from_dict
@pytest.mark.inference
class TestInferenceConfig(DistributedTest):
world_size = 1
def test_overlap_kwargs(self):
config = {"replace_with_kernel_inject": True}
... | 1,429 | 34.75 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/inference/test_model_profiling.py | import os
import time
import pytest
import torch
import deepspeed
from transformers import pipeline
from unit.common import DistributedTest
@pytest.fixture
def query(model, task):
if task == "text-generation":
return "DeepSpeed is"
elif task == "fill-mask":
if "roberta" in model:
r... | 2,867 | 31.224719 | 78 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/inference/test_inference.py | import os
import time
import torch
import pytest
import itertools
import deepspeed
from deepspeed.git_version_info import torch_info
from unit.common import DistributedTest
from packaging import version as pkg_version
from deepspeed.ops.op_builder import OpBuilder
from transformers import pipeline
from transformers.mod... | 15,479 | 32.147752 | 120 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/inference/test_checkpoint_sharding.py | import os
import pytest
import torch
import deepspeed
from deepspeed.model_implementations import DeepSpeedTransformerInference
from transformers import AutoConfig, AutoModelForCausalLM
from unit.common import DistributedTest, DistributedFixture
def check_dtype(model, expected_dtype):
def find_dtype(module):
... | 3,379 | 34.578947 | 83 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/pipe/test_pipe_module.py | import copy
import torch
import torch.nn as nn
import deepspeed.comm as dist
import pytest
import deepspeed
from deepspeed.pipe import PipelineModule
from deepspeed.utils import RepeatingLoader
from unit.common import DistributedTest
HIDDEN_DIM = 32
LAYERS = 8
@pytest.fixture
def sequential_model():
model = ... | 2,700 | 26.561224 | 69 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/sparse_attention/test_sparse_attention.py | # DeepSpeed note, some parts of code taken & adapted from commit c368a9fd1b2c9dee4cc94de9a6bb0be3d447be41
# https://github.com/ptillet/torch-blocksparse/blob/master/tests/test_softmax.py
# https://github.com/ptillet/torch-blocksparse/blob/master/tests/test_matmul.py
# https://github.com/ptillet/torch-blocksparse/blob/m... | 9,369 | 36.935223 | 129 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/aio/test_aio.py | import pytest
import os
import filecmp
import torch
import deepspeed
import deepspeed.comm as dist
from deepspeed.ops.aio import AsyncIOBuilder
from unit.common import DistributedTest
MEGA_BYTE = 1024**2
BLOCK_SIZE = MEGA_BYTE
QUEUE_DEPTH = 2
IO_SIZE = 16 * MEGA_BYTE
IO_PARALLEL = 2
if not deepspeed.ops.__compatible_... | 8,381 | 35.12931 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/cuda/test_cuda_forward.py | import math
import numpy as np
import torch
import pytest
import random
import copy
from torch import nn
from unit.modelingpreln import BertEncoder as BertEncoderPreln
from unit.modeling import BertLayerNorm, BertConfig, BertEncoder as BertEncoderPostln
from deepspeed import DeepSpeedTransformerLayer, DeepSpeedTransfor... | 13,118 | 39.119266 | 110 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/cuda/test_cuda_backward.py | import math
import numpy as np
import torch
import pytest
import random
import copy
from torch import nn
from deepspeed import DeepSpeedTransformerLayer, DeepSpeedTransformerConfig
from unit.modeling import BertConfig, BertLayerNorm, BertEncoder as BertEncoderPostln
from unit.modelingpreln import BertEncoder as BertEnc... | 12,952 | 36.985337 | 106 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/adam/test_cpu_adam.py | import torch
import numpy as np
import pytest
from cpuinfo import get_cpu_info
import deepspeed
from deepspeed.ops.adam import FusedAdam
from deepspeed.ops.op_builder import CPUAdamBuilder
if not deepspeed.ops.__compatible_ops__[CPUAdamBuilder.NAME]:
pytest.skip("cpu-adam is not compatible", allow_module_level=Tr... | 3,086 | 34.079545 | 82 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/adam/test_adamw.py | import deepspeed
import torch
import pytest
from deepspeed.ops.adam import FusedAdam
from deepspeed.ops.adam import DeepSpeedCPUAdam
from unit.common import DistributedTest
from unit.simple_model import SimpleModel
# yapf: disable
#'optimizer, zero_offload, torch_adam, adam_w_mode, resulting_optimizer
adam_configs = ... | 2,922 | 40.169014 | 82 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/quantizer/test_fake_quantization.py | import torch
import pytest
from deepspeed.ops import op_builder
quantizer_cuda_module = None
def allclose(x, y):
assert x.dtype == y.dtype
rtol, atol = {torch.float32: (2e-2, 5e-3), torch.float16: (2e-2, 5e-3)}[x.dtype]
return torch.allclose(x, y, rtol=rtol, atol=atol)
def quantize_dequantize_ref(input... | 2,370 | 37.868852 | 100 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/quantizer/test_dequantize.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import pytest
import torch
from deepspeed.ops import op_builder
quantize_module = None
def int4x2to2xint4(int4X2tensor):
high = int4X2tensor >> 4
low = (int4X2tensor << 4) >> 4
return torch.stack((high, low), dim=-1).flatten()
def run_quantize(data, ... | 3,112 | 31.427083 | 94 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/quantizer/test_quantize.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import pytest
import torch
from deepspeed.ops import op_builder
inference_module = None
def run_quantize_ds(activations, num_groups, q_bits, is_symmetric_quant):
global inference_module
if inference_module is None:
inference_module = op_builder.Qua... | 8,197 | 35.435556 | 139 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/adagrad/test_cpu_adagrad.py | import torch
import numpy as np
import pytest
import deepspeed
from deepspeed.ops.adagrad import DeepSpeedCPUAdagrad
from deepspeed.ops.op_builder import CPUAdagradBuilder
if not deepspeed.ops.__compatible_ops__[CPUAdagradBuilder.NAME]:
pytest.skip("cpu-adagrad is not compatible", allow_module_level=True)
def c... | 5,074 | 36.043796 | 81 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/spatial/test_nhwc_bias_add.py | '''
Copyright 2022 The Microsoft DeepSpeed Team
'''
import pytest
import torch
from deepspeed.ops.transformer.inference.bias_add import nhwc_bias_add
def allclose(x, y):
assert x.dtype == y.dtype
rtol, atol = {torch.float32: (5e-3, 5e-4), torch.float16: (3e-2, 2e-3), torch.int8: (1, 1)}[x.dtype]
return t... | 4,275 | 33.764228 | 104 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/transformer/inference/test_moe_res_matmult.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this system",
allow_module_level=Tru... | 1,980 | 33.754386 | 85 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/transformer/inference/test_bias_geglu.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this system",
allow_module_level=Tru... | 1,772 | 33.096154 | 104 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/transformer/inference/test_layer_norm.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import deepspeed
import torch
import pytest
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this system",
allow_module_level=Tru... | 7,757 | 40.935135 | 112 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/transformer/inference/test_residual_add.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this system",
allow_module_level=Tru... | 4,723 | 33.992593 | 88 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/transformer/inference/test_bias_add.py | import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this system",
allow_module_level=True)
inference_module = None
torch_minor_version = Non... | 1,654 | 32.77551 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/transformer/inference/test_bias_gelu.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this system",
allow_module_level=Tru... | 2,263 | 33.30303 | 97 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/unit/ops/transformer/inference/test_bias_relu.py | """
Copyright 2022 The Microsoft DeepSpeed Team
"""
import pytest
import torch
import deepspeed
from deepspeed.ops.op_builder import InferenceBuilder
if not deepspeed.ops.__compatible_ops__[InferenceBuilder.NAME]:
pytest.skip("Inference ops are not available on this system",
allow_module_level=Tru... | 1,852 | 32.690909 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/perf/adam_test1.py | import torch
from deepspeed.ops.adam import DeepSpeedCPUAdam
import time
device = 'cpu'
model_size = 1 * 1024**3
param = torch.nn.Parameter(torch.ones(model_size, device=device))
param_fp16 = torch.nn.Parameter(torch.ones(model_size,
dtype=torch.half,
... | 724 | 30.521739 | 65 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/perf/adam_test.py | import torch
from deepspeed.ops.adam import DeepSpeedCPUAdam
import time
device = 'cpu'
model_size = 1 * 1024**3
group_size = [model_size, 274432]
param = [torch.nn.Parameter(torch.ones(size, device=device)) for size in group_size]
optimizer = DeepSpeedCPUAdam(param)
#torch.set_num_threads(128)
for i, p in enumerate(... | 750 | 29.04 | 84 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/small_model_debugging/test.py | import torch
from deepspeed.pt.deepspeed_linear import LinearModuleForZeroStage3
from deepspeed.pt.log_utils import logger
def see_memory_usage(message):
# Print message except when distributed but not rank 0
logger.info(message)
logger.info(
"Memory Allocated %s GigaBytes ",
torch.cuda.m... | 1,304 | 26.765957 | 93 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/small_model_debugging/test_model.py | import os
import json
import argparse
import torch
import deepspeed
from torch.utils.data.distributed import DistributedSampler
import deepspeed.comm as dist
class SimpleModel(torch.nn.Module):
def __init__(self, hidden_dim, empty_grad=False):
super(SimpleModel, self).__init__()
self.linear = torc... | 3,616 | 29.91453 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/small_model_debugging/stage3_test.py | import torch
import deepspeed
###################################
# Setup
###################################
class VerboseLinear(torch.nn.Linear):
def __init__(self, **kwargs):
print(f'Begin VerboseLinear.__init__')
super().__init__(**kwargs)
print(f'End VerboseLinear.__init__')
class... | 2,425 | 26.885057 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/onebit/test_nccl_backend.py | import torch
import deepspeed.comm as dist
import numpy as np
import argparse
import deepspeed
import os
from deepspeed.runtime.comm.nccl import NcclBackend
parser = argparse.ArgumentParser()
parser.add_argument('--local_rank', type=int, default=-1)
args = parser.parse_args()
deepspeed.init_distributed(dist_backend=... | 3,309 | 35.777778 | 109 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/onebit/test_mpi_backend.py | from mpi4py import MPI
import torch
import deepspeed.comm as dist
import numpy as np
import deepspeed
from deepspeed.runtime.comm.mpi import MpiBackend
comm = MPI.COMM_WORLD
size = comm.Get_size()
rank = comm.Get_rank()
deepspeed.init_distributed(dist_backend='nccl')
# Change cuda_aware to True to test out CUDA-Awa... | 3,211 | 37.238095 | 109 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/onebit/test_nccl_perf.py | import torch
import deepspeed.comm as dist
import numpy as np
import argparse
import deepspeed
import os
from deepspeed.runtime.comm.nccl import NcclBackend
from deepspeed.utils.timer import SynchronizedWallClockTimer
from statistics import mean
timers = SynchronizedWallClockTimer()
parser = argparse.ArgumentParser(... | 2,959 | 30.489362 | 89 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/onebit/test_mpi_perf.py | from mpi4py import MPI
import torch
import deepspeed
from deepspeed.runtime.comm.mpi import MpiBackend
# Configure wall clock timer
from deepspeed.utils.timer import SynchronizedWallClockTimer
from statistics import mean
timers = SynchronizedWallClockTimer()
comm = MPI.COMM_WORLD
size = comm.Get_size()
rank = comm... | 2,086 | 27.986111 | 83 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/lightning/test_simple.py | import torch
from pytorch_lightning import LightningModule, Trainer
from pytorch_lightning.strategies import DeepSpeedStrategy
from torch.utils.data import DataLoader, Dataset
class RandomDataset(Dataset):
def __init__(self, size, length):
self.len = length
self.data = torch.randn(length, size)
... | 1,553 | 26.75 | 90 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/tests/model/Megatron_GPT2/run_func_test.py | # Copyright (c) 2019, The Microsoft DeepSpeed Team. All rights reserved.
#
# Note: please copy webtext data to "Megatron-LM" folder, before running this script.
import unittest
import os
import re
from .test_common import BaseTestCase
LAYERS = 2
HIDDEN_SIZE = 128
ATTN_HEADS = 8
SEQ_LEN = 64
MASTER_PORT = 29700
def ... | 19,246 | 30.865894 | 92 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/csrc/aio/py_test/ds_aio_handle.py | """
Copyright 2020 The Microsoft DeepSpeed Team
Licensed under the MIT license.
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import torch
import os
import time
from multiprocessing import Pool, Barrier
from deepspeed.ops.aio import AsyncIOBuilder
from test_ds_aio_utils import report... | 5,080 | 27.706215 | 98 | py |
FlexGen | FlexGen-main/benchmark/third_party/DeepSpeed/csrc/aio/py_test/ds_aio_basic.py | """
Copyright 2020 The Microsoft DeepSpeed Team
Licensed under the MIT license.
Functionality of swapping optimizer tensors to/from (NVMe) storage devices.
"""
import torch
import os
import time
from deepspeed.ops.aio import AsyncIOBuilder
from multiprocessing import Pool, Barrier
from test_ds_aio_utils import report... | 4,262 | 28.4 | 98 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/conftest.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 2,739 | 34.128205 | 107 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/setup.py | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 15,179 | 33.189189 | 157 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/hubconf.py | # Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 8,496 | 51.450617 | 189 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/longform-qa/eli5_app.py | import datasets
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
import faiss
import transformers
from eli5_utils import (
embed_questions_for_retrieval,
make_qa_s2s_model,
qa_s2s_generate,
query_es_index,
query_qa_dense_index,
)
from transformers impor... | 13,474 | 37.28125 | 159 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/longform-qa/eli5_utils.py | import functools
import math
import os # noqa: F401
from random import choice, randint
from time import time
import datasets # noqa: F401
import numpy as np
import pandas as pd
import torch
import torch.utils.checkpoint as checkpoint
from elasticsearch import Elasticsearch # noqa: F401
from elasticsearch.helpers im... | 28,287 | 40.056604 | 119 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/codeparrot/scripts/codeparrot_training.py | import logging
import os
import time
from argparse import Namespace
from pathlib import Path
import datasets
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from torch.utils.data.datapipes.iter.... | 12,866 | 38.348624 | 116 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/codeparrot/scripts/validation_loss.py | import logging
import torch
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from accelerate import Accelerator
from arguments import EvaluationArguments
from transformers import AutoModelForCausalLM, AutoTokenizer, HfArgumentParser, set... | 3,496 | 33.97 | 114 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/codeparrot/scripts/human_eval.py | import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from tqdm import tqdm
import transformers
from accelerate import Accele... | 9,006 | 38.331878 | 118 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/self-training-text-classification/selftraining.py | # coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 16,963 | 42.609254 | 119 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/self-training-text-classification/finetuning.py | # coding=utf-8
# Copyright 2022 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 34,604 | 41.616995 | 119 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/bertology/run_prune_gpt.py | #!/usr/bin/env python3
""" This script is adapted from the Bertology pruning code (https://github.com/huggingface/transformers/blob/783d7d2629e97c5f0c5f9ef01b8c66410275c204/examples/research_projects/bertology/run_bertology.py)
to prune GPT-like models. The author is @altsoph.
"""
import argparse
import logging
import... | 15,497 | 38.535714 | 204 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/bertology/run_bertology.py | #!/usr/bin/env python3
# Copyright 2018 CMU and The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | 18,600 | 40.06181 | 118 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/use_own_knowledge_dataset.py | import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import torch
from datasets import Features, Sequence, Value, load_dataset
import faiss
from transformers import (
DPRCo... | 8,257 | 38.32381 | 144 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/utils_rag.py | import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from transfo... | 8,114 | 32.122449 | 118 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/finetune_rag.py | """Finetuning script for RAG models. Adapted from examples.seq2seq.finetune.py"""
import argparse
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Any, Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
import... | 26,214 | 39.330769 | 119 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/distributed_pytorch_retriever.py | import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
logger = logging.getLogger(__name__)
class RagPyTorchDistributedRetriever(RagRetriever):
"""
A distributed retriever built on top of ... | 6,539 | 46.05036 | 155 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/test_distributed_retriever.py | import json
import os
import shutil
import sys
import tempfile
import unittest
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
import faiss
from transformers import BartConfig, BartTokenizer, DPRConfig, DPRQuestionEncoderTokenizer, RagConfig
from transform... | 13,794 | 39.693215 | 118 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/eval_rag.py | """ Evaluation script for RAG models."""
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as trans... | 11,211 | 33.928349 | 119 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/lightning_base.py | import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelForQuestionAnswering,
... | 15,637 | 37.612346 | 124 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/callbacks_rag.py | import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def count_trainable_parameters(model):
model_parame... | 4,443 | 36.661017 | 116 | py |
FlexGen | FlexGen-main/benchmark/third_party/transformers/examples/research_projects/rag/_test_finetune_rag.py | import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
logging.ba... | 3,953 | 34.621622 | 85 | py |
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